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modifying the shade of the composite

Kolor + is a filled paste containing the same components as Herculite XRV (Herculite XRV received market clearance under 510(k) K943642). The material is highly pigmented in eleven distinct shades by incorporation of the same pigments employed in XRV. The dentist will utilize this material by adding a small portion (1 - 2 drops) to a composite filling material. This effects the material only in coloration. Since the components of Kolor + are identical to XRV and the ratio of components are similar, the addition of this colorant has no discernible affect upon the performance of the composite material.

The provided text describes a medical device called Kolor+ which is intended to be a colorant for composite filling materials. The text does not describe any acceptance criteria for device performance, nor does it detail any study that proves the device meets such criteria in the context of typical AI/ML-based device evaluation (e.g., diagnostic accuracy, sensitivity, specificity).

The document focuses on:

• Material Equivalence: Kolor+ shares components with Herculite XRV (previously cleared device).
• Intended Use Equivalence: Kolor+ is similar to other existing colorants/shade modifiers.
• Physical Property Comparison: A comparison of physical properties to three predicate devices is mentioned, with results in Exhibit E. However, the details of these comparisons or what constitutes "acceptance criteria" for these physical properties are not provided in the given text.
• Biocompatibility: Cytotoxicity testing was performed on Kolor+, determining it was "non-toxic." Further biocompatibility testing was deemed unnecessary due to the shared components with Herculite XRV.

Therefore, I cannot provide the requested information in the format of AI/ML device evaluation metrics, as it is not present in the provided input.

However, I can interpret the available information relative to the implied acceptance criteria and "study" described in the context of a 510(k) submission for a non-AI medical device.

Interpretation based on the provided text (for a non-AI device):

1. A table of acceptance criteria and the reported device performance:

Note: The actual numerical acceptance limits for physical properties (e.g., flexural strength, wear resistance) are not provided in this summary but would typically be present in Exhibit E. The "performance" mentioned is in the context of the physical properties of the composite material post-colorant addition, not diagnostic algorithmic performance.

2. Sample size used for the test set and the data provenance:

• Cytotoxicity Test: Sample size not specified.
• Physical Properties Comparison: Not explicitly stated how many samples were tested for physical properties comparison.
• Provenance: Not specified.

3. Number of experts used to establish the ground truth for the test set and the qualifications of those experts:

• Not applicable in the context of this device type and type of evaluation described. Physical property testing and biocompatibility assessments are typically performed by laboratory technicians/scientists following validated protocols, not "experts establishing ground truth" in the diagnostic sense.

4. Adjudication method for the test set:

• Not applicable.

5. If a multi reader multi case (MRMC) comparative effectiveness study was done, If so, what was the effect size of how much human readers improve with AI vs without AI assistance:

• Not applicable as this is not an AI/ML diagnostic device.

6. If a standalone (i.e. algorithm only without human-in-the-loop performance) was done:

• Not applicable as this is not an AI/ML diagnostic device.

7. The type of ground truth used (expert consensus, pathology, outcomes data, etc):

• For Biocompatibility: Laboratory test results (cytotoxicity). The "ground truth" is established by a standardized biological response test.
• For Physical Properties: Measured physical attributes of the material (e.g., strength, hardness, etc.) compared against established benchmarks or predicate device performance.

8. The sample size for the training set:

• Not applicable as this is not an AI/ML device.

9. How the ground truth for the training set was established:

• Not applicable as this is not an AI/ML device.

In summary, the provided text describes a regulatory submission for a material-based medical device, not an AI/ML device. Therefore, the concepts of "acceptance criteria" and "studies" are applied to material properties and biocompatibility, not to diagnostic accuracy or algorithm performance as is typical for AI/ML products.

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